Hydraulic modelling of inland urban flooding: Recent advances
•Research in urban flood modelling has received a major attention in last 4 years.•The topics cover flow process understanding and innovation in numerical modelling.•Many new experimental set-ups and numerical models were developed.•Innovative calculations aim at improving prediction quality or effi...
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| Published in: | Journal of hydrology (Amsterdam) Vol. 609; p. 127763 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01.06.2022
Elsevier BV |
| Subjects: | |
| ISSN: | 0022-1694, 1879-2707, 1879-2707 |
| Online Access: | Get full text |
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| Summary: | •Research in urban flood modelling has received a major attention in last 4 years.•The topics cover flow process understanding and innovation in numerical modelling.•Many new experimental set-ups and numerical models were developed.•Innovative calculations aim at improving prediction quality or efficiency.•Challenges remain for an efficient and precise urban flood calculations.
This review provides a synthesis of advances in our understanding of urban flood processes and their modelling over the last four years (2018–2021). Four aspects are covered: knowledge of urban flood flow and transport processes, stability of humans and objects within flooded streets, reliability of computational modelling and approaches for speeding-up computations of urban flood event. New laboratory setups have shed light on previously unexplored processes such as flow intrusion into buildings or contaminant exchanges between surface and underground drainage. The stability of a single pedestrians or object (e.g., vehicles, waste containers) under urban flooding was analysed, but not group effects such as clogging. Improvements in computations were achieved by new strategies for merging and processing various sources of high quality topographic and forcing data (e.g., precipitation), the incorporation of more and more details on the drainage systems (e.g., effect of gullies), and 3D instead of 2D simulations. Computational efficiency was enhanced based on massive parallelization, adaptive mesh, porosity models, surrogate models as well as machine learning. Finally crowd-sourced data are shown to offer an avenue for next generation model validation methods. Remaining knowledge gaps and guidance for future research are proposed and predict that additional research work will be performed in following years. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 13. Climate action scopus-id:2-s2.0-85129772460 |
| ISSN: | 0022-1694 1879-2707 1879-2707 |
| DOI: | 10.1016/j.jhydrol.2022.127763 |